In this paper we present application of genetic programming (GP) [1] to evolution of indirect encoding of neural network weights. We compare usage of original HyperNEAT algorithm w...
Data Mining with Bayesian Network learning has two important characteristics: under broad conditions learned edges between variables correspond to causal influences, and second, f...
Ioannis Tsamardinos, Constantin F. Aliferis, Alexa...
Existing data mining techniques mostly focus on finding global patterns and lack the ability to systematically discover regional patterns. Most relationships in spatial datasets ar...
Oner Ulvi Celepcikay, Christoph F. Eick, Carlos Or...
We present an efficient protocol for privacy-preserving evaluation of diagnostic programs, represented as binary decision trees or branching programs. The protocol applies a bran...
Justin Brickell, Donald E. Porter, Vitaly Shmatiko...
Stochastic relational models (SRMs) [15] provide a rich family of choices for learning and predicting dyadic data between two sets of entities. The models generalize matrix factor...